There has been a huge hue and cry about the unavailability of consumer data with the Indian utilities. However, the question that needs to be asked is that whether we have really made an effort to collect the right data set? And if we have, do we have the processes to continuously update the database and maintain it?
In this post, I've tried to list down baby-steps that would go a long way in creating a reliable and comprehensive customer database through the Consumer Indexing (CI) process.
# 1 Create consensus on how the data is required across the teams within utility
A lot needs to be done to really come to a common consensus across the utility stakeholders about how the utility plans to use the consumer data, not just to create a database because it's a mandate in the contract. This would also require the utility to project and decide how the data will be maintained finally when the utility operations smoothen up in due course.
Further, one also needs to take a call on what data is the priority and when and how it will be collected.
# 2 Create a methodology to collect the data
Now, most widely used methodology currently adopted is the consumer surveys or consumer indexing, as many call it. However, the whole process is extremely tedious and static. One needs to think destructively to really create a methodology which will be, not just fast, but also reliable enough to feed data continuously to the other internal teams.
This could encompass use of social media to really entice and engage the customers to voluntarily post their data and update their data.
What precaution needs to be taken is to adopt a infrastructure to really accept data from multiple sources and consolidate the same into one piece of data.
# 3 Support systems needs to be designed and put in place to receive and organize the customer data
As the process of consumer data upgradation picks up pace, the utility should really be ready to receive huge chunks of data from various sources - viz. legacy systems, new connections, on-field checks, consumer indexing process, social media, etc.
I believe that MS Excel is fairly strong a tool to manage such data, provided the data structure is correctly created. At the same time, appropriate end-to-end integration needs to be done for the data collection methodology.
# 4 Selecting the right tool for the right data
GIS systems, though being one of the latest of technologies adopted by the utilities, has a major drawback. The data once imported into a GIS system is static. A GIS system will always take only that data as input that you'll feed to the system without doing any sanity check.
Now this creates a major loop hole in the system that can only be fixed by selecting a robust tool for data collection. This tool should also take into account that at times, the data might need to be collected from the field. Our experience in the field of customer data collection has proved that even a simple smart phone integrated with web-based forms is good enough. However, a well-designed consumer survey form is the easiest of all techniques used to initially populate the customer database.
Once the base-data is ready, the Billing Centers and Customer Care Centers should be developed to act as the nodal touch-points to gather the customer data on a more regular process.
# 5 Create the right training and monitoring modules
Even with the best of the methods and tools, without a systematic training and monitoring methodology, a good consumer indexing process could go for a toss. Right tools for training, and data audits are indispensable parts of the CI process
One of the speakers at the recently concluded India Utility Knowledge and Networking Conference (12-Feb-2013, New Delhi) pointed out that the utilities will go slow when it comes to adoption of technology and partner with smaller, local players to help them roll out the operations. We believe that there is a whole lot of internal thinking that needs to go in to really ensure that the utilities hit the ground running. Lack of clarity from the utility, coupled with the inefficiencies of the local players could kill the effort spent in the consumer indexing process.
Further readings: Putting your best foot forward - Best Practices in Consumer Indexing
In this post, I've tried to list down baby-steps that would go a long way in creating a reliable and comprehensive customer database through the Consumer Indexing (CI) process.
# 1 Create consensus on how the data is required across the teams within utility
A lot needs to be done to really come to a common consensus across the utility stakeholders about how the utility plans to use the consumer data, not just to create a database because it's a mandate in the contract. This would also require the utility to project and decide how the data will be maintained finally when the utility operations smoothen up in due course.
Further, one also needs to take a call on what data is the priority and when and how it will be collected.
# 2 Create a methodology to collect the data
Now, most widely used methodology currently adopted is the consumer surveys or consumer indexing, as many call it. However, the whole process is extremely tedious and static. One needs to think destructively to really create a methodology which will be, not just fast, but also reliable enough to feed data continuously to the other internal teams.
This could encompass use of social media to really entice and engage the customers to voluntarily post their data and update their data.
What precaution needs to be taken is to adopt a infrastructure to really accept data from multiple sources and consolidate the same into one piece of data.
# 3 Support systems needs to be designed and put in place to receive and organize the customer data
As the process of consumer data upgradation picks up pace, the utility should really be ready to receive huge chunks of data from various sources - viz. legacy systems, new connections, on-field checks, consumer indexing process, social media, etc.
I believe that MS Excel is fairly strong a tool to manage such data, provided the data structure is correctly created. At the same time, appropriate end-to-end integration needs to be done for the data collection methodology.
# 4 Selecting the right tool for the right data
GIS systems, though being one of the latest of technologies adopted by the utilities, has a major drawback. The data once imported into a GIS system is static. A GIS system will always take only that data as input that you'll feed to the system without doing any sanity check.
Now this creates a major loop hole in the system that can only be fixed by selecting a robust tool for data collection. This tool should also take into account that at times, the data might need to be collected from the field. Our experience in the field of customer data collection has proved that even a simple smart phone integrated with web-based forms is good enough. However, a well-designed consumer survey form is the easiest of all techniques used to initially populate the customer database.
Once the base-data is ready, the Billing Centers and Customer Care Centers should be developed to act as the nodal touch-points to gather the customer data on a more regular process.
# 5 Create the right training and monitoring modules
Even with the best of the methods and tools, without a systematic training and monitoring methodology, a good consumer indexing process could go for a toss. Right tools for training, and data audits are indispensable parts of the CI process
One of the speakers at the recently concluded India Utility Knowledge and Networking Conference (12-Feb-2013, New Delhi) pointed out that the utilities will go slow when it comes to adoption of technology and partner with smaller, local players to help them roll out the operations. We believe that there is a whole lot of internal thinking that needs to go in to really ensure that the utilities hit the ground running. Lack of clarity from the utility, coupled with the inefficiencies of the local players could kill the effort spent in the consumer indexing process.
Further readings: Putting your best foot forward - Best Practices in Consumer Indexing
